The edge computing license plate reader for access controls to car parks and low emission zones (ZBE)

LPR Edge Computing provides artificial intelligence to Bosch Inteox cameras. As its name suggests (License Plate Recognition) is a license plate recognition application that focuses on parking management and access control applications. This license plate reader in APP format is more agile, thanks to the edge computing architecture, it is easily configurable and can be integrated with other applications.


What novelties does this LPR bring?

The license plate reading system is already something that has existed on the market for years, however, the main novelty that this APP brings is edge computing technology, this means that unlike most existing solutions, our application does not transmits the video stream, but rather processes it in the camera itself and only sends metadata, thus improving response times, eliminating a stable Internet connection while saving bandwidth, reducing installation costs and infrastructure and also takes data privacy into account.


LPR features

Advantages of using SNGULAR's LPR Artificial Intelligence as a license plate reader

The installation of LPR Edge Computing in your Bosch Inteox camera will provide your license plate reader system with the following features or added values:

  • Instant license plate reader

    In just a few milliseconds and with a success rate of 95%.

  • Edge computing

    Video processing in the camera itself, sends only metadata.

  • Admission and exclusion list

    Choose who can and cannot enter your parking lot or restricted access area.

  • Custom integration

    Designed for Bosch Inteox and BVMS cameras, it also allows the integration of custom APIs.

Where is LPR Edge Computing applied?

Initially, the LPR Edge Computing application is configured to solve:

  • Access control to parking lots, public and private.

  • Access control to low emission zones (LEZ).

  • Control at charging points and gas stations.

How does LPR Edge Computing work?

The application uses deep learning models divided into two main steps and two key points:

  • Detección

    It detects the license plate in the video transmission and generates its coordinates in the image.

  • Recognition

    It uses these coordinates to extract the license plate image and read the characters from it.

  • High accuracy

    Between both layers, we use advanced image processing techniques to achieve high accuracy in a multitude of scenarios.

  • Integración

    The information processed throughout the application can be sent to your own video management system or other applications for further use.

Where can I get LPR Edge Computing?

Now available in the Azena Application Store!

LPR Edge Computing by SNGULAR has been available since March 2022 on the Azena Application Store, initially for Spain and Portugal, with an interesting introductory offer, and the option to download a free 30-day trial version.



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Any question about LPR Edge Computing?

Contact with our team,
we love hearing from you

Do you have an idea that can't wait? Any questions about LPR Edge Computing? o Do you just want to make a comment about the application? Do not hesitate to contact us through the contact form or through the email address:




We will be happy to answer any of your questions.


Why working with Sngular?

We are more than developers, IoT and Artificial Intelligence tailored to your projects

License plate recognition applications can be quite complex and cumbersome to configure for specific use cases. That is why SNGULAR, in collaboration with BOSCH Engineering, has designed a specific application for parking and access control use cases that can be easily configured according to your specific needs, which provides artificial intelligence to your license plate reader system and streamlines through edge computing architecture. Our AI (artificial intelligence) team will be happy to answer your technical queries, as well as implement any customizations you may need for your specific use cases.

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